Abstract
A fundamental part of flood risk management is the detection of potential flood susceptible areas. This research presents a GIS-based probabilistic framework for flood susceptibility mapping. The main advantage of the method proposed is the integration of probabilistic approach and ordered weighted averaging (OWA) to take into account the impact of the uncertainty in criteria weights and different risk attitudes of the decision maker via Monte Carlo simulation. The probabilistic GIS-OWA approach is used in a case study of evaluating susceptibility conditions in Gucheng County, central China. The spatial database includes digital elevation model (DEM), slope (SL), maximum three-day precipitation (M3DP), topographic wetness index (TWI), distance from the river (Dr), Soil Conservation Service Curve Number (SCS-CN). The results demonstrate that further improvement in the robustness of flood susceptibility evaluation can be achieved by articulating the presence of uncertainty included in criteria weights and exploring the influence of risk attitude on decision-making.
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